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    Please use this identifier to cite or link to this item: https://ir.lib.ncu.edu.tw/handle/987654321/107482


    Title: Investigation of multiple human factors in personalized learning
    Authors: 陳攸華;Chen, Sherry Y.;Huang, Pei-Ren;Shih, Yu-Cheng;Chang, Li-Ping
    Contributors: 資訊電機學院網路學習科技研究所
    Keywords: Cognitive Style;cognitive styles;College Students;Colleges & universities;Education reform;Educational Technology;Foreign Countries;Gender aspects;Gender Differences;Human factors;Individualized Instruction;Learning;Lifelong learning;Navigation (Information Systems);personalized learning;prior knowledge;Prior Learning;Questionnaires;Student Characteristics;Student Reaction;Taiwan;Teaching Methods;Technology Uses in Education;Web Based Instruction;web-based Learning
    Date: 2016-01-02
    Issue Date: 2026-04-23 14:14:12 (UTC+8)
    Publisher: Taylor and Francis Ltd.;Abingdon: Routledge
    Abstract: 摘要: In the past decade, a number of personalized learning systems have been developed and they mainly focus on learners' prior knowledge. On the other hand, previous research suggested that gender differences and cognitive styles have great effects on student learning. To this end, this study examines how human factors, especially gender differences and cognitive styles, affect learners' reactions to a personalized and non-personalized learning systems based on learners' prior knowledge. Forty-four university students participated in this study. The results show that females and Serialists show positive reactions to the personalized learning system, while males and Holists demonstrate similar reactions to the personalized learning system and the non-personalized learning system. The implications of these results for the design of personalized learning systems are discussed.
    出版者: Abingdon: Routledge
    出版日期: 2016-01-02
    出處: Interactive learning environments, 2016-01, Vol.24 (1), p.119-141
    資源來源: Taylor & Francis Journals Auto-Holdings Collection
    版權: 2013 Taylor & Francis 2013
    版權: 2013 Taylor & Francis
    識別號: ISSN: 1049-4820
    識別號: EISSN: 1744-5191
    識別號: DOI: 10.1080/10494820.2013.825809
    Appears in Collections:[Graduate Institute of Network Learning Technology] journal & Dissertation

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